Triple

T20092676
Position Surface form Disambiguated ID Type / Status
Subject Togoshi E496311 entity
Predicate partOf P40 FINISHED
Object Kanto region NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kanto region | Statement: [Togoshi, partOf, Kanto region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanto region
Context triple: [Togoshi, partOf, Kanto region]
  • A. Kanto
    Kanto is a major geographical and metropolitan region of eastern Japan that includes Tokyo and several surrounding prefectures.
  • B. Kanto Plain
    The Kanto Plain is Japan's largest and most populous lowland region, encompassing Tokyo and surrounding urban and agricultural areas on central Honshu.
  • C. Chubu region of Japan
    The Chubu region of Japan is a central area on Japan’s main island of Honshu, encompassing diverse landscapes from the Japanese Alps to coastal plains and including major cities such as Nagoya.
  • D. Jetisu Region
    Jetisu Region is an administrative region in southeastern Kazakhstan known for its mountainous landscapes and historical role as part of the larger Almaty area.
  • E. Kantō region chosen
    The Kantō region is a major geographical and economic area of eastern Honshu, Japan, encompassing Tokyo and several surrounding prefectures and serving as the country’s political and population center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66668db8881908c43b1deef9af1d3 completed April 20, 2026, 5:46 p.m.
Created at: April 11, 2026, 11:22 p.m.